Browsing by Author "Habib, Ashraf S"

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    Computerized surveillance of opioid-related adverse drug events in perioperative care: a cross-sectional study.
    (Patient Saf Surg, 2009-08-11) Eckstrand, Julie A; Habib, Ashraf S; Williamson, Abbie; Horvath, Monica M; Gattis, Katherine G; Cozart, Heidi; Ferranti, Jeffrey
    BACKGROUND: Given the complexity of surgical care, perioperative patients are at high risk of opioid-related adverse drug events. Existing methods of detection, such as trigger tools and manual chart review, are time-intensive which makes sustainability challenging. Using strategic rule design, computerized surveillance may be an efficient, pharmacist-driven model for event detection that leverages existing staff resources. METHODS: Computerized adverse drug event surveillance uses a logic-based rules engine to identify potential adverse drug events or evolving unsafe clinical conditions. We extended an inpatient rule (administration of naloxone) to detect opioid-related oversedation and respiratory depression to perioperative care at a large academic medical center. Our primary endpoint was the adverse drug event rate. For all patients with a naloxone alert, manual chart review was performed by a perioperative clinical pharmacist to assess patient harm. In patients with confirmed oversedation, other patient safety event databases were queried to determine if they could detect duplicate, prior, or subsequent opioid-related events. RESULTS: We identified 419 cases of perioperative naloxone administration. Of these, 101 were given postoperatively and 69 were confirmed as adverse drug events after chart review yielding a rate of 1.89 adverse drug events/1000 surgical encounters across both the inpatient and ambulatory settings. Our ability to detect inpatient opioid adverse drug events increased 22.7% by expanding surveillance into perioperative care. Analysis of historical surveillance data as well as a voluntary reporting database revealed that 11 of our perioperative patients had prior or subsequent harmful oversedation. Nine of these cases received intraoperative naloxone, and 2 had received naloxone in the post-anesthesia care unit. Pharmacist effort was approximately 3 hours per week to evaluate naloxone alerts and confirm adverse drug events. CONCLUSION: A small investment of resources into a pharmacist-driven surveillance model gave great gains in organizational adverse drug event detection. The patients who experienced multiple events are particularly relevant to future studies seeking risk factors for opioid induced respiratory depression. Computerized surveillance is an efficient, impactful, and sustainable model for ongoing capture and analysis of these rare, but potentially serious events.
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    Development and Validation of a Model for Opioid Prescribing Following Gynecological Surgery.
    (JAMA network open, 2022-07) Rodriguez, Isabel V; Cisa, Paige McKeithan; Monuszko, Karen; Salinaro, Julia; Habib, Ashraf S; Jelovsek, J Eric; Havrilesky, Laura J; Davidson, Brittany

    Importance

    Overprescription of opioid medications following surgery is well documented. Current prescribing models have been proposed in narrow patient populations, which limits their generalizability.

    Objective

    To develop and validate a model for predicting outpatient opioid use following a range of gynecological surgical procedures.

    Design, setting, and participants

    In this prognostic study, statistical models were explored using data from a training cohort of participants undergoing gynecological surgery for benign and malignant indications enrolled prospectively at a single institution's academic gynecologic oncology practice from February 2018 to March 2019 (cohort 1) and considering 39 candidate predictors of opioid use. Final models were internally validated using a separate testing cohort enrolled from May 2019 to February 2020 (cohort 2). The best final model was updated by combining cohorts, and an online calculator was created. Data analysis was performed from March to May 2020.

    Exposures

    Participants completed a preoperative survey and weekly postoperative assessments (up to 6 weeks) following gynecological surgery. Pain management was at the discretion of clinical practitioners.

    Main outcomes and measures

    The response variable used in model development was number of pills used postoperatively, and the primary outcome was model performance using ordinal concordance and Brier score.

    Results

    Data from 382 female adult participants (mean age, 56 years; range, 18-87 years) undergoing gynecological surgery (minimally invasive procedures, 158 patients [73%] in cohort 1 and 118 patients [71%] in cohort 2; open surgical procedures, 58 patients [27%] in cohort 1 and 48 patients [29%] in cohort 2) were included in model development. One hundred forty-seven patients (38%) used 0 pills after hospital discharge, and the mean (SD) number of pills used was 7 (10) (median [IQR], 3 [0-10] pills). The model used 7 predictors: age, educational attainment, smoking history, anticipated pain medication use, anxiety regarding surgery, operative time, and preoperative pregabalin administration. The ordinal concordance was 0.65 (95% CI, 0.62-0.68) for predicting 5 or more pills (Brier score, 0.22), 0.65 (95% CI, 0.62-0.68) for predicting 10 or more pills (Brier score, 0.18), and 0.65 (95% CI, 0.62-0.68) for predicting 15 or more pills (Brier score, 0.14).

    Conclusions and relevance

    This model provides individualized estimates of outpatient opioid use following a range of gynecological surgical procedures for benign and malignant indications with all model inputs available at the time of procedure closing. Implementation of this model into the clinical setting is currently ongoing, with plans for additional validation in other surgical populations.
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    Incidence, patient satisfaction, and perceptions of post-surgical pain: results from a US national survey.
    (Curr Med Res Opin, 2014-01) Gan, Tong J; Habib, Ashraf S; Miller, Timothy E; White, William; Apfelbaum, Jeffrey L
    OBJECTIVE: During the past two decades, professional associations, accrediting bodies, and payors have made post-surgical pain treatment a high priority. In light of the disappointing findings in previous surveys, a survey was conducted to assess patient perceptions and characterize patient experiences/levels of satisfaction with post-surgical pain management. RESEARCH DESIGN AND METHODS: Survey included a random sample of US adults who had undergone surgery within 5 years from the survey date. Participants were asked about their concerns before surgery, severity of perioperative pain, pain treatments, perceptions about post-surgical pain and pain medications, and satisfaction with treatments they received. RESULTS: Of the 300 participants, ∼86% experienced pain after surgery; of these, 75% had moderate/extreme pain during the immediate post-surgical period, with 74% still experiencing these levels of pain after discharge. Post-surgical pain was the most prominent pre-surgical patient concern, and nearly half reported they had high/very high anxiety levels about pain before surgery. Approximately 88% received analgesic medications to manage pain; of these, 80% experienced adverse effects and 39% reported moderate/severe pain even after receiving their first dose. STUDY LIMITATIONS: Key study limitations include the relatively small population size, potential for recall bias associated with the 14-month average time delay from surgery date to survey date, and the inability to account for influences of type of surgery and intraoperative anesthetic/analgesic use on survey results. CONCLUSIONS: Despite heightened awareness and clinical advancements in pain management, there has been little improvement in post-surgical analgesia as measured by this survey of post-surgical patients.
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